--- title: "Who cites Forest-of-Thought: Scaling — 42 citing papers" description: "42 papers of the Elamur Research library cite «Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning», found in their…" canonical: "https://research.elamur.ai/free/en/papers/bi-2024-forest-thought-scaling-test-time/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/bi-2024-forest-thought-scaling-test-time/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Forest-of-Thought: Scaling Test-Time Compute for…](https://md.research.elamur.ai/free/en/papers/bi-2024-forest-thought-scaling-test-time/) / cited by # Who cites «Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning» 42 papers of our library cite it (of the 149,439 whose bibliographies we read) · 17 with a page here, the most cited first · [← back to «Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning»](https://md.research.elamur.ai/free/en/papers/bi-2024-forest-thought-scaling-test-time/) 1. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations* 2. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/) 3. [**Cumulative Reasoning with Large Language Models arXiv:2308.04371**Yifan Zhang, Jingqin Yang, Yang Yuan, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-cumulative-reasoning-large-language-models/) 4. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/) 5. **[APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay](https://md.research.elamur.ai/free/en/papers/prabhakar-2025-apigen-mt-agentic-pipeline-multi/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Akshara Prabhakar, Zuxin Liu, Ming Zhu, et al.*2025 · 36 citations* 6. **[NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neurons](https://md.research.elamur.ai/free/en/papers/dong-2026-neureasoner-explainable-controllable-unified-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haonan Dong, Kehan Jiang, Haoran Ye, et al.*2026 · 13 citations* 7. **[Dynamic Parallel Tree Search for Efficient LLM Reasoning](https://md.research.elamur.ai/free/en/papers/ding-2025-dynamic-parallel-tree-search-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifu Ding, Wentao Jiang, Shunyu Liu, et al.*2025 · 13 citations* 8. [**Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition arXiv:2505.22375**Hanting Chen, Yasheng Wang, Kai Han, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-pangu-embedded-efficient-dual/) 9. **[Learning from Diverse Reasoning Paths with Routing and Collaboration](https://md.research.elamur.ai/free/en/papers/lei-2025-learning-diverse-reasoning-paths-routing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenyu Lei, Zhen Tan, Song Wang, et al.*2025 · 11 citations* 10. **[OctoTools: A Multi-Agent Framework with Extensible Tools for Complex Reasoning](https://md.research.elamur.ai/free/en/papers/lu-2026-octotools-multi-agent-framework-extensible/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pan Lu, Bowen Chen, Sheng Liu, et al.*2026 · 5 citations* 11. **[Large Language Model-Enhanced Multi-Armed Bandits](https://md.research.elamur.ai/free/en/papers/sun-2026-large-language-model-enhanced-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiahang Sun, Zhiyong Wang, Runhan Yang, et al.*2026 · 1 citation* 12. [**From Test-taking to Cognitive Scaffolding: A Pedagogical Diagnostic Benchmark for LLMs on English Standardized Tests arXiv:2505.17056**Luoxi Tang, Tharunya Sundar, Yuqiao Meng, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/tang-2025-test-taking-cognitive-scaffolding-pedagogical/) 13. **[CLARO: Controlled Attribute-Driven Reasoning Optimization for Efficient Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/schlesinger-2026-claro-controlled-attribute-driven-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oded Schlesinger, Young Kyung Kim, J. Matias Di Martino, et al.*2026* 14. **[Format-Adapter: Improving Reasoning Capability of LLMs by Adapting Suitable Format](https://md.research.elamur.ai/free/en/papers/wang-2026-format-adapter-improving-reasoning-capability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dingzirui Wang, Xuanliang Zhang, Rongyu Cao, et al.*2026* 15. **[Self-Reflective Generation at Test Time](https://md.research.elamur.ai/free/en/papers/mu-2026-self-reflective-generation-test-time/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jian Mu, Qixin Zhang, Zhiyong Wang, et al.*2026* 16. **[Time-for-Accuracy: Formalizing Chain-of-Thought as an Expansion of Logical Depth](https://md.research.elamur.ai/free/en/papers/wang-2026-time-accuracy-formalizing-chain-thought/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yue Wang, Zhi Zhang, Wang Xi, et al.*2026* 17. **[TRACE: An Experiential Framework for Coherent Multi-hop Knowledge Graph Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2026-trace-experiential-framework-coherent-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingxu Wang, Jiaxin Huang, Mengzhu Wang, et al.*2026* 25 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/bi-2024-forest-thought-scaling-test-time/) — Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning